Estimating surface fluxes using eddy covariance and numerical ogive optimization

Jakob Sievers; T. Papakyriakou; S.E. Larsen; Mathilde Manon Jammet; Søren Rysgaard; Mikael Kristian Sejr; L.L. Sørensen

doi:10.5194/acp-15-2081-2015

Estimating surface fluxes using eddy covariance and numerical ogive optimization

Jakob Sievers, T. Papakyriakou, S.E. Larsen, Mathilde Manon Jammet, Søren Rysgaard, Mikael Kristian Sejr, L.L. Sørensen

LUKKET: Geografi

13 Citationer (Scopus)

927 Downloads (Pure)

Abstract

Estimating representative surface fluxes using eddy covariance leads invariably to questions concerning inclusion or exclusion of low-frequency flux contributions. For studies where fluxes are linked to local physical parameters and up-scaled through numerical modelling efforts, low-frequency contributions interfere with our ability to isolate local biogeochemical processes of interest, as represented by turbulent fluxes. No method currently exists to disentangle low-frequency contributions on flux estimates. Here, we present a novel comprehensive numerical scheme to identify and separate out low-frequency contributions to vertical turbulent surface fluxes. For high flux rates (|Sensible heat flux| > 40 Wm ^-2, |latent heat flux|> 20 Wm ^-2 and |CO₂ flux|> 100 mmol m ^-2 d ^-1 we found that the average relative difference between fluxes estimated by ogive optimization and the conventional method was low (5-20%) suggesting negligible low-frequency influence and that both methods capture the turbulent fluxes equally well. For flux rates below these thresholds, however, the average relative difference between flux estimates was found to be very high (23-98%) suggesting non-negligible low-frequency influence and that the conventional method fails in separating low-frequency influences from the turbulent fluxes. Hence, the ogive optimization method is an appropriate method of flux analysis, particularly in low-flux environments.

Originalsprog	Engelsk
Tidsskrift	Atmospheric Chemistry and Physics
Vol/bind	15
Sider (fra-til)	2081-2103
Antal sider	23
ISSN	1680-7316
DOI	https://doi.org/10.5194/acp-15-2081-2015
Status	Udgivet - 26 feb. 2015

Adgang til dokumentet

10.5194/acp-15-2081-2015

Estimating surface fluxes using eddy covariance and numerical ogive optimizationForlagets udgivne version, 12,5 MB

http://www.atmos-chem-phys.net/15/2081/2015/

Citationsformater

@article{4595e852f8c249b69fe018a9913550de,

title = "Estimating surface fluxes using eddy covariance and numerical ogive optimization",

abstract = "Estimating representative surface fluxes using eddy covariance leads invariably to questions concerning inclusion or exclusion of low-frequency flux contributions. For studies where fluxes are linked to local physical parameters and up-scaled through numerical modelling efforts, low-frequency contributions interfere with our ability to isolate local biogeochemical processes of interest, as represented by turbulent fluxes. No method currently exists to disentangle low-frequency contributions on flux estimates. Here, we present a novel comprehensive numerical scheme to identify and separate out low-frequency contributions to vertical turbulent surface fluxes. For high flux rates (|Sensible heat flux| > 40 Wm -2, |latent heat flux|> 20 Wm -2 and |CO2 flux|> 100 mmol m -2 d -1 we found that the average relative difference between fluxes estimated by ogive optimization and the conventional method was low (5-20%) suggesting negligible low-frequency influence and that both methods capture the turbulent fluxes equally well. For flux rates below these thresholds, however, the average relative difference between flux estimates was found to be very high (23-98%) suggesting non-negligible low-frequency influence and that the conventional method fails in separating low-frequency influences from the turbulent fluxes. Hence, the ogive optimization method is an appropriate method of flux analysis, particularly in low-flux environments.",

author = "Jakob Sievers and T. Papakyriakou and S.E. Larsen and Jammet, {Mathilde Manon} and S{\o}ren Rysgaard and Sejr, {Mikael Kristian} and L.L. S{\o}rensen",

note = "CENPERMOA[2015] ",

year = "2015",

month = feb,

day = "26",

doi = "10.5194/acp-15-2081-2015",

language = "English",

volume = "15",

pages = "2081--2103",

journal = "Atmospheric Chemistry and Physics",

issn = "1680-7316",

publisher = "Copernicus GmbH",

}

TY - JOUR

T1 - Estimating surface fluxes using eddy covariance and numerical ogive optimization

AU - Sievers, Jakob

AU - Papakyriakou, T.

AU - Larsen, S.E.

AU - Jammet, Mathilde Manon

AU - Rysgaard, Søren

AU - Sejr, Mikael Kristian

AU - Sørensen, L.L.

N1 - CENPERMOA[2015]

PY - 2015/2/26

Y1 - 2015/2/26

N2 - Estimating representative surface fluxes using eddy covariance leads invariably to questions concerning inclusion or exclusion of low-frequency flux contributions. For studies where fluxes are linked to local physical parameters and up-scaled through numerical modelling efforts, low-frequency contributions interfere with our ability to isolate local biogeochemical processes of interest, as represented by turbulent fluxes. No method currently exists to disentangle low-frequency contributions on flux estimates. Here, we present a novel comprehensive numerical scheme to identify and separate out low-frequency contributions to vertical turbulent surface fluxes. For high flux rates (|Sensible heat flux| > 40 Wm -2, |latent heat flux|> 20 Wm -2 and |CO2 flux|> 100 mmol m -2 d -1 we found that the average relative difference between fluxes estimated by ogive optimization and the conventional method was low (5-20%) suggesting negligible low-frequency influence and that both methods capture the turbulent fluxes equally well. For flux rates below these thresholds, however, the average relative difference between flux estimates was found to be very high (23-98%) suggesting non-negligible low-frequency influence and that the conventional method fails in separating low-frequency influences from the turbulent fluxes. Hence, the ogive optimization method is an appropriate method of flux analysis, particularly in low-flux environments.

AB - Estimating representative surface fluxes using eddy covariance leads invariably to questions concerning inclusion or exclusion of low-frequency flux contributions. For studies where fluxes are linked to local physical parameters and up-scaled through numerical modelling efforts, low-frequency contributions interfere with our ability to isolate local biogeochemical processes of interest, as represented by turbulent fluxes. No method currently exists to disentangle low-frequency contributions on flux estimates. Here, we present a novel comprehensive numerical scheme to identify and separate out low-frequency contributions to vertical turbulent surface fluxes. For high flux rates (|Sensible heat flux| > 40 Wm -2, |latent heat flux|> 20 Wm -2 and |CO2 flux|> 100 mmol m -2 d -1 we found that the average relative difference between fluxes estimated by ogive optimization and the conventional method was low (5-20%) suggesting negligible low-frequency influence and that both methods capture the turbulent fluxes equally well. For flux rates below these thresholds, however, the average relative difference between flux estimates was found to be very high (23-98%) suggesting non-negligible low-frequency influence and that the conventional method fails in separating low-frequency influences from the turbulent fluxes. Hence, the ogive optimization method is an appropriate method of flux analysis, particularly in low-flux environments.

U2 - 10.5194/acp-15-2081-2015

DO - 10.5194/acp-15-2081-2015

M3 - Journal article

SN - 1680-7316

VL - 15

SP - 2081

EP - 2103

JO - Atmospheric Chemistry and Physics

JF - Atmospheric Chemistry and Physics

ER -

Estimating surface fluxes using eddy covariance and numerical ogive optimization

Abstract

Adgang til dokumentet

Fingeraftryk

Citationsformater